Scurfy Mice Develop Features of Connective Tissue Disease Overlap Syndrome and Mixed Connective Tissue Disease in the Absence of Regulatory T Cells
Bibliographic record
Abstract
gene, scurfy mice are deficient in functional regulatory T cells (Treg). The consequent loss of peripheral tolerance manifests itself by fatal autoimmune mediated multi-organ disease. Previous studies have outlined the systemic inflammatory disease and demonstrated production of anti-nuclear antibodies (ANA) in scurfy mice. However, specific autoantibody targets remained to be defined. ANA are immunological markers for several connective tissue diseases (CTD) and target a large number of intracellular molecules. Therefore, we examined scurfy sera for the presence of different ANA specificities and further assessed the organ involvement in these animals. Indirect immunofluorescence was used as a screen for ANA in the sera of scurfy mice and dilutions of 1/100 were considered positive. Addressable laser bead immunoassays (ALBIA) were used to detect specific autoantibody targets. Subsequent histological tissue evaluation was verified by hematoxylin and eosin (H&E) staining. In our study, we observed that nearly all scurfy mice produced ANA. The most prevalent pattern in scurfy sera was nuclear coarse speckled, also known as the AC-5 pattern according to the International Consensus on ANA Patterns. U1-ribonucleoprotein (U1RNP) was found to be the most common target antigen recognized by autoantibodies in scurfy mice. Additionally, scurfy mice exhibited a mild myositis with histological characteristics similar to polymyositis/dermatomyositis. Myopathy-specific autoantibody profile revealed significantly increased levels of anti-SMN (survival of motor neuron) as well as anti-Gemin3 antibodies in scurfy sera. Overall, we demonstrate that the impaired peripheral tolerance in the absence of regulatory T cells in scurfy mice is associated with features of mixed connective tissue disease (MCTD). This includes, along with our previous findings, very high titers of anti-U1RNP antibodies and an inflammatory myopathy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".